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USS-reward-model-exp6-grl-only
athirorg/USS-reward-model-exp6-grl-only
USS-reward-model-exp6-grl-only is a machine learning model from athirorg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- modernbert
- Access
- Public
- Created
- Jun 3, 2026
- Updated
- Jun 3, 2026
- SHA
- 16fd8de0
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
USS-reward-model-exp6-grl-only
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.4503
- Mse: 0.1857
- Mae: 0.3335
- R2: 0.0374
- Spearman Correlation: 0.2772
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 10
- total_train_batch_size: 20
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Spearman Correlation |
|---|---|---|---|---|---|---|---|
| 11.3890 | 1.0 | 97 | 0.1401 | 0.1999 | 0.3675 | -0.0365 | -0.0219 |
| 1.5946 | 2.0 | 194 | 0.1645 | 0.2008 | 0.3874 | -0.0410 | 0.1877 |
| 12.8941 | 3.0 | 291 | 3.9913 | 1.2837 | 1.0346 | -5.6549 | 0.1595 |
| 47.4786 | 4.0 | 388 | 5.2619 | 0.3131 | 0.4203 | -0.6231 | 0.1512 |
| 52.6400 | 5.0 | 485 | 5.2644 | 0.6928 | 0.7324 | -2.5916 | 0.2834 |
| 47.2109 | 6.0 | 582 | 4.4503 | 0.1857 | 0.3335 | 0.0374 | 0.2772 |
| 40.5784 | 7.0 | 679 | 3.8972 | 0.3032 | 0.4734 | -0.5721 | 0.2260 |
| 34.6866 | 8.0 | 776 | 3.3503 | 0.2189 | 0.3854 | -0.1347 | 0.3143 |
| 30.7190 | 9.0 | 873 | 3.0725 | 0.2011 | 0.3632 | -0.0425 | 0.2707 |
| 28.8300 | 10.0 | 970 | 2.9724 | 0.1929 | 0.3394 | -0.0003 | 0.2642 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Jun 3, 2026
- Updated
- Jun 3, 2026